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Who cites Carissa Schoenick

2,131 citations of their works from 2,111 papers of our library (of the 149,439 whose bibliographies we read) · 532 with a page here, the most cited first · page 2 of 6 · 101–200 · ← Carissa Schoenick

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  1. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  2. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
  3. InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and EfficiencyarXiv:2508.18265Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.2025 · 179 citations
  4. What Makes Reading Comprehension Questions Easier?Conference on Empirical Methods in Natural Language Processing (EMNLP)Saku Sugawara, Kentaro Inui, Satoshi Sekine, et al.2018 · 179 citations
  5. Large Language Diffusion ModelsConference on Neural Information Processing Systems (NeurIPS)Shen Nie, Fengqi Zhu, Zebin You, et al.2025 · 178 citations
  6. What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction TuningarXiv:2312.15685Wei Liu, Weihao Zeng, Keqing He, et al.2023 · 178 citations
  7. Does it Make Sense? And Why? A Pilot Study for Sense Making and ExplanationAnnual Meeting of the Association for Computational Linguistics (ACL)Cunxiang Wang, Shuailong Liang, Yue Zhang, et al.2019 · 174 citations
  8. Improving Machine Reading Comprehension with General Reading StrategiesConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Kai Sun, Dian Yu, Dong Yu, et al.2019 · 172 citations
  9. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
  10. Orca 2: Teaching Small Language Models How to ReasonarXiv:2311.11045Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.2023 · 162 citations
  11. From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction TuningarXiv:2308.12032Ming Li, Yong Zhang, Zhitao Li, et al.2023 · 161 citations
  12. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
  13. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessACM Transactions on Intelligent Systems and TechnologyFali Wang, Zhiwei Zhang, Xianren Zhang, et al.2024 · 159 citations
  14. Chameleon: Mixed-Modal Early-Fusion Foundation ModelsarXiv:2405.09818Chameleon Team2024 · 159 citations
  15. Jamba: A Hybrid Transformer-Mamba Language ModelarXiv:2403.19887Opher Lieber, Barak Lenz, Hofit Bata, et al.2024 · 159 citations
  16. SemEval-2020 Task 4: Commonsense Validation and ExplanationInternational Workshop on Semantic Evaluation (SemEval)Cunxiang Wang, Shuailong Liang, Yili Jin, et al.2020 · 158 citations
  17. Moshi: a speech-text foundation model for real-time dialoguearXiv:2410.00037Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.2024 · 157 citations
  18. Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
  19. LayerSkip: Enabling Early Exit Inference and Self-Speculative DecodingAnnual Meeting of the Association for Computational Linguistics (ACL)Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, et al.2024 · 156 citations
  20. Atom: Low-bit Quantization for Efficient and Accurate LLM ServingMLSys 2024Yilong Zhao, Chien-Yu Lin, Kan Zhu, et al.2023 · 156 citations
  21. Iterative Reasoning Preference OptimizationConference on Neural Information Processing Systems (NeurIPS)Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.2024 · 153 citations
  22. Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 152 citations
  23. Searching for Best Practices in Retrieval-Augmented GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaohua Wang, Zhenghua Wang, Xuan Gao, et al.2024 · 150 citations
  24. OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceChanghun Lee, Jungyu Jin, Taesu Kim, et al.2023 · 149 citations
  25. RA-DIT: Retrieval-Augmented Dual Instruction TuningarXiv:2310.01352Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.2023 · 149 citations
  26. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
  27. Context-faithful Prompting for Large Language ModelsFindings of the Association for Computational LinguisticsWenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.2023 · 148 citations
  28. LongRoPE: Extending LLM Context Window Beyond 2 Million TokensarXiv:2402.13753Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, et al.2024 · 142 citations
  29. Beat the AI: Investigating Adversarial Human Annotation for Reading ComprehensionTransactions of the Association for Computational Linguistics (TACL)Max Bartolo, Alastair Roberts, Johannes Welbl, et al.2020 · 141 citations
  30. Self-Alignment with Instruction BacktranslationarXiv:2308.06259Xian Li, Ping Yu, Chunting Zhou, et al.2023 · 139 citations
  31. Representing Numbers in NLP: a Survey and a VisionConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Avijit Thawani, Jay Pujara, Filip Ilievski, et al.2021 · 139 citations
  32. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningarXiv:2409.12183Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.2024 · 138 citations
  33. DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal UnderstandingarXiv:2412.10302Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.2024 · 137 citations
  34. Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and ApproachesarXiv:1904.01172Shane Storks, Qiaozi Gao, Joyce Y. Chai2019 · 135 citations
  35. EuroLLM: Multilingual Language Models for EuropearXiv:2409.16235Pedro Henrique Martins, Patrick Fernandes, Joao Alves, et al.2024 · 133 citations
  36. Knowledge Unlearning for Mitigating Privacy Risks in Language ModelsarXiv:2210.01504Joel Jang, Dongkeun Yoon, Sohee Yang, et al.2022 · 131 citations
  37. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  38. Natural Language Reasoning, A SurveyACM Computing SurveysFei Yu, Hongbo Zhang, Prayag Tiwari, et al.2023 · 130 citations
  39. Fanar: An Arabic-Centric Multimodal Generative AI PlatformarXiv:2501.13944Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.2025 · 127 citations
  40. Faithful Reasoning Using Large Language ModelsarXiv:2208.14271Antonia Creswell, Murray Shanahan2022 · 122 citations
  41. QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM ServingMLSys 2025Yujun Lin, Haotian Tang, Shang Yang, et al.2024 · 120 citations
  42. SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language ModelsFindings of the Association for Computational LinguisticsLijun Li, Bowen Dong, Ruohui Wang, et al.2024 · 119 citations
  43. ExT5: Towards Extreme Multi-Task Scaling for Transfer LearningarXiv:2111.10952Vamsi Aribandi, Yi Tay, Tal Schuster, et al.2021 · 114 citations
  44. ALLaM: Large Language Models for Arabic and EnglisharXiv:2407.15390M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.2024 · 113 citations
  45. Don't Make Your LLM an Evaluation Benchmark CheaterarXiv:2311.01964Kun Zhou, Yutao Zhu, Zhipeng Chen, et al.2023 · 112 citations
  46. RLHF Workflow: From Reward Modeling to Online RLHFarXiv:2405.07863Hanze Dong, Wei Xiong, Bo Pang, et al.2024 · 111 citations
  47. Nemotron-4 340B Technical ReportarXiv:2406.11704Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.2024 · 107 citations
  48. Pixtral 12BarXiv:2410.07073Pravesh Agrawal, Szymon Antoniak, Emma Bou Hanna, et al.2024 · 107 citations
  49. ChatGPT Is a Knowledgeable but Inexperienced Solver: An Investigation of Commonsense Problem in Large Language ModelsLanguage Resources and Evaluation Conference (LREC)Ning Bian, Xianpei Han, Le Sun, et al.2024 · 106 citations
  50. A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and RecommendationsConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.2024 · 105 citations
  51. LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale InstructionsarXiv:2304.14402Minghao Wu, Abdul Waheed, Chiyu Zhang, et al.2023 · 105 citations
  52. HEAD-QA: A Healthcare Dataset for Complex ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)David Vilares, Carlos Gómez-Rodríguez2019 · 105 citations
  53. Tokenizer Choice For LLM Training: Negligible or Crucial?Findings of the Association for Computational LinguisticsMehdi Ali, Michael Fromm, Klaudia Thellmann, et al.2024 · 104 citations
  54. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 103 citations
  55. Large language models for education: A survey and outlookWang2024 · 101 citations
  56. Rationale-Augmented Ensembles in Language ModelsarXiv:2207.00747Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.2022 · 101 citations
  57. LongAlign: A Recipe for Long Context Alignment of Large Language ModelsarXiv:2401.18058Yushi Bai, Xin Lv, Jiajie Zhang, et al.2024 · 98 citations
  58. Make Your LLM Fully Utilize the ContextConference on Neural Information Processing Systems (NeurIPS)Shengnan An, Zexiong Ma, Zeqi Lin, et al.2024 · 97 citations
  59. MAmmoTH2: Scaling Instructions from the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Yue, Tuney Zheng, Ge Zhang, et al.2024 · 96 citations
  60. Language Ranker: A Metric for Quantifying LLM Performance Across High and Low-Resource LanguagesProceedings of the AAAI Conference on Artificial IntelligenceZihao Li, Yucheng Shi, Zirui Liu, et al.2024 · 95 citations
  61. Boosting Language Models Reasoning with Chain-of-Knowledge PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianing Wang, Qiushi Sun, Xiang Li, et al.2024 · 94 citations
  62. Proving Test Set Contamination in Black Box Language ModelsarXiv:2310.17623Yonatan Oren, Nicole Meister, Niladri Chatterji, et al.2023 · 92 citations
  63. “My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language ModelsFindings of the Association for Computational LinguisticsXinpeng Wang, Bolei Ma, Chengzhi Hu, et al.2024 · 91 citations
  64. Skywork: A More Open Bilingual Foundation ModelarXiv:2310.19341Tianwen Wei, Liang Zhao, Lichang Zhang, et al.2023 · 91 citations
  65. Rephrasing the Web: A Recipe for Compute and Data-Efficient Language ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Pratyush Maini, Skyler Seto, Richard Bai, et al.2024 · 90 citations
  66. RQ-RAG: Learning to Refine Queries for Retrieval Augmented GenerationarXiv:2404.00610Chi-Min Chan, Chunpu Xu, Ruibin Yuan, et al.2024 · 90 citations
  67. WorldTree: A Corpus of Explanation Graphs for Elementary Science Questions supporting Multi-hop InferenceLanguage Resources and Evaluation Conference (LREC)Peter Jansen, Elizabeth Wainwright, Steven Marmorstein, et al.2018 · 90 citations
  68. Dream 7B: Diffusion Large Language ModelsarXiv:2508.15487Jiacheng Ye; Zhihui Xie; Lin Zheng; Jiahui Gao; Zirui Wu; Xin Jiang; Zhenguo Li;, Lingpeng Kong2025 · 89 citations
  69. How to Train Long-Context Language Models (Effectively)Annual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 89 citations
  70. Massive Activations in Large Language ModelsarXiv:2402.17762Mingjie Sun, Xinlei Chen, J. Zico Kolter, et al.2024 · 88 citations
  71. Small Language Models: Survey, Measurements, and InsightsarXiv:2409.15790Zhenyan Lu, Xiang Li, Dongqi Cai, et al.2024 · 88 citations
  72. Reinforcement Learning for Reasoning in Large Language Models with One Training ExampleConference on Neural Information Processing Systems (NeurIPS)Yiping Wang, Qing Yang, Zhiyuan Zeng, et al.2025 · 87 citations
  73. Machine Unlearning of Pre-trained Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jin Yao, Eli Chien, Minxin Du, et al.2024 · 86 citations
  74. Benchmark Data Contamination of Large Language Models: A SurveyarXiv:2406.04244Cheng Xu, Shuhao Guan, Derek Greene, et al.2024 · 85 citations
  75. LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-TrainingConference on Empirical Methods in Natural Language Processing (EMNLP)Tong Zhu, Xiaoye Qu, Daize Dong, et al.2024 · 85 citations
  76. SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural ReasoningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bin Wang, Zhengyuan Liu, Xin Huang, et al.2024 · 85 citations
  77. Extreme Compression of Large Language Models via Additive QuantizationInternational Conference on Machine Learning (ICML)Vage Egiazarian, Andrei Panferov, Denis Kuznedelev, et al.2024 · 84 citations
  78. Improving Alignment and Robustness with Circuit BreakersConference on Neural Information Processing Systems (NeurIPS)Andy Zou, Long Phan, Justin Wang, et al.2024 · 83 citations
  79. Mitigating the Alignment Tax of RLHFConference on Empirical Methods in Natural Language Processing (EMNLP)Yong Lin, Hangyu Lin, Wei Xiong, et al.2024 · 83 citations
  80. Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal ModelarXiv:2408.11039Chunting Zhou, Lili Yu, Arun Babu, et al.2024 · 83 citations
  81. PRD: Peer Rank and Discussion Improve Large Language Model based EvaluationsarXiv:2307.02762Ruosen Li, Teerth Patel, Xinya Du2023 · 83 citations
  82. EfficientQAT: Efficient Quantization-Aware Training for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mengzhao Chen, Wenqi Shao, Peng Xu, et al.2025 · 82 citations
  83. Knowledge Fusion of Large Language ModelsarXiv:2401.10491Fanqi Wan, Xinting Huang, Deng Cai, et al.2024 · 82 citations
  84. Smaug: Fixing Failure Modes of Preference Optimisation with DPO-PositivearXiv:2402.13228Arka Pal, Deep Karkhanis, Samuel Dooley, et al.2024 · 82 citations
  85. Rainier: Reinforced Knowledge Introspector for Commonsense Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Jiacheng Liu, Skyler Hallinan, Ximing Lu, et al.2022 · 82 citations
  86. D4: Improving LLM Pretraining via Document De-Duplication and DiversificationConference on Neural Information Processing Systems (NeurIPS)Kushal Tirumala, Daniel Simig, Armen Aghajanyan, et al.2023 · 81 citations
  87. QuaRTz: An Open-Domain Dataset of Qualitative Relationship QuestionsarXiv:1909.03553Oyvind Tafjord, Matt Gardner, Kevin Lin, et al.2019 · 81 citations
  88. AudioBench: A Universal Benchmark for Audio Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bin Wang, Xunlong Zou, Geyu Lin, et al.2025 · 77 citations
  89. FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation ResearcharXiv:2405.13576Jiajie Jin, Yutao Zhu, Guanting Dong, et al.2024 · 77 citations
  90. SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-ScalingarXiv:2312.15166Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.2023 · 77 citations
  91. KMMLU: Measuring Massive Multitask Language Understanding in KoreanConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Guijin Son, Hanwool Lee, Sungdong Kim, et al.2025 · 76 citations
  92. Self-Reflection in LLM Agents: Effects on Problem-Solving PerformancearXiv:2405.06682 · 2nd International Conference on Foundation and Large Language Models (FLLM 2024), pp. 476-483Matthew Renze, Erhan Guven2024 · 76 citations
  93. PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics CapabilitiesSettaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.2024 · 75 citations
  94. INCLUDE: Evaluating Multilingual Language Understanding with Regional KnowledgearXiv:2411.19799Angelika Romanou, Negar Foroutan, Anna Sotnikova, et al.2024 · 74 citations
  95. QuRating: Selecting High-Quality Data for Training Language ModelsarXiv:2402.09739Alexander Wettig, Aatmik Gupta, Saumya Malik, et al.2024 · 74 citations
  96. ReFT: Representation Finetuning for Language ModelsConference on Neural Information Processing Systems (NeurIPS)Zhengxuan Wu, Aryaman Arora, Zheng Wang, et al.2024 · 74 citations
  97. When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model LeaderboardsarXiv:2402.01781Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay, et al.2024 · 74 citations
  98. Instruction Mining: Instruction Data Selection for Tuning Large Language ModelsarXiv:2307.06290Yihan Cao, Yanbin Kang, Chi Wang, et al.2023 · 74 citations
  99. What Language Model to Train if You Have One Million GPU Hours?arXiv:2210.15424Teven Le Scao, Thomas Wang, Daniel Hesslow, et al.2022 · 73 citations
  100. A Dataset for Statutory Reasoning in Tax Law Entailment and Question AnsweringarXiv:2005.05257Nils Holzenberger, Andrew Blair-Stanek, Benjamin Van Durme2020 · 73 citations

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